Telemetry is no longer a passive infrastructure tool. It is becoming a compounding liability that CTOs and CFOs are only beginning to understand. As AI systems both produce and consume telemetry, the data collected for one purpose now feeds automated decisions, raising costs, governance risks and exposure that traditional approaches cannot manage.

What You Need to Know

Telemetry volumes have tripled in many enterprises over the past year, with agentic AI expected to drive nearly 10x more growth within two years. The data is treated as an asset, but its retention costs, security obligations and discovery risk are often overlooked. When AI systems consume telemetry and feed back into operations, the data becomes a body of knowledge that no single person fully understands. CTOs and CFOs need to shift from viewing telemetry as pure infrastructure to treating it as a governed, finite resource with clear expiration dates.

When AI Consumes Its Own Telemetry

Traditional telemetry was retrospective. It described what happened after the fact. In modern AI systems, telemetry takes on a dual role. A session log captured to troubleshoot a crash today may become training data tomorrow, evolve into a model feature later and eventually drive automated decisions without human oversight. The same data serves multiple functions throughout its lifecycle, many of which have little to do with why it was collected.

This creates a feedback loop. The system produces telemetry, the AI consumes it, which generates new signals and predictions, and those create an appetite for still more telemetry. The value organizations place on data keeps growing, often ahead of any clear understanding of how it will be used. Once telemetry becomes a form of organizational memory, the conversation shifts from observability to governance, cost and control.

The Asymmetry of Retention Decisions

Organizations tend to keep everything. The cost of storing another terabyte feels small compared with the hypothetical cost of discarding data that might have been a golden ticket. But this reasoning ignores the liabilities. Every retained dataset carries ongoing storage and governance costs, security and compliance obligations, and discovery risk if litigation arises.

Asking whether data could be useful someday is not helpful. Almost anything clears that bar. A better question is what specific capability it is being kept for. If there is a clear answer, retain the data and govern it accordingly. If not, the expected benefits of keeping it do not outweigh the costs and risks of holding it.

Two Blind Spots for CTOs and CFOs

For CTOs, the blind spot is treating telemetry growth as a scaling problem. Ingestion pipelines, storage and query speed matter, but the real risk is that telemetry turns into a body of knowledge no single person understands. The math is unforgiving. Every new data source can be matched against every source already in place, creating combinations that are no longer tractable. A clickstream, session length, support ticket and device ID are harmless alone. Combined, they can reconstruct daily routines, flag financial changes or predict life events. Sensitivity is born out of correlation, not individual streams. The thing to worry about is whether you can still explain what your organization knows and where that knowledge came from.

For CFOs, the blind spot is filing telemetry under infrastructure cost. Telemetry compounds in ways other infrastructure does not. More data feeds more AI, which demands more data, which drives storage costs, compute costs and compliance overhead. The cost structure is not linear. It is exponential. Filing telemetry as a simple line item obscures the real financial exposure. The true cost includes the people needed to govern it, the legal risk of ungoverned data and the opportunity cost of retaining data that adds no value.

Why This Matters

The consequences of ignoring telemetry as a liability are mounting. For CTOs, the inability to explain what the organization knows creates regulatory risk and makes it impossible to bound downstream use. For CFOs, unmanaged telemetry growth leads to budget overruns and hidden liabilities that can surface during audits or litigation. Both roles face a future where telemetry is no longer a technical detail but a strategic risk that demands clear ownership, purpose and expiration dates for every data stream. Organizations that fail to treat telemetry as a governed resource will find themselves paying for data they cannot control and cannot afford to keep.

  • Assign ownership: Every telemetry stream needs a designated owner, a stated purpose and an expiration date.
  • Audit correlations: Evaluate what combined data streams can reveal, not just individual ones.
  • Model cost as compound: Budget for telemetry as an exponential cost, not a linear one, to avoid surprises.